1. Field of the Invention
The present invention relates to an image signal coding device, and more particularly to an image signal coding device for outputting image information while coding the same into variable length codes and also adding error detection and correction codes thereto.
2. Related Background Art
Recently, highly efficient coding technology of information has been developed and a high degree of compression has been realized in the field of digital transmission of color images.
With such progress, images of good quality can be transmitted and received via transmission lines even at a low data rate. On the contrary, an error of one word occurring on transmission lines causes a larger influence upon images. For this reason, some measures are required for coping with code errors occurring on transmission lines by using an error detection code, an error correction code, or the like.
Particularly, when using transmission lines, such as magnetic recording media and communication satellites, where transmission quality is expected to deteriorate, special consideration should be paid to the measures taken for compensating for such code errors.
FIG. 1 is a block diagram showing a schematic configuration of a conventional image transmitting and receiving system.
In FIG. 1, denoted at 101 is a terminal to which an image signal is input. The image signal inputted through the terminal 101 is converted into digital form by an analog-to-digital (hereinafter abbreviated as A/D) converter 102. The digitized image signal is coded by a highly efficient coding circuit 103 for being compressed in the amount (band) of information.
The image information compressed by the coding circuit 103 is supplied to an error correction coding circuit 104 where a parity check bit for correcting a code error is added thereto (for the purpose of error correction coding), followed by delivery to a transmission line 105.
On the receiving side, a string of data received via the transmission line 105 is once stored in a memory 106, and an error correction unit 107 accessible to the memory 106 carries out correction of the code error by using the parity check bit. The image information subjected to the code error correction is output from the memory 106 and applied to a highly efficient decoding circuit 108. The decoding circuit 108 performs the process reversed to that of the above highly efficient coding circuit 103 for expanding the amount (band) of information to restore the original digital image signal. This digital image signal is converted into analog form by a digital-to-analog (hereinafter abbreviated as D/A) converter 109 and then delivered as an analog image signal from a terminal 110.
As to the configuration of the highly efficient coding circuit 103, i.e., the image compressing technique, in FIG. 1, there have been proposed a variety of methods. More specifically, the so-called ADCT method is proposed as a typical one of color image coding techniques. The ADCT method is described in detail in an article by Takahiro Saito, et al., "Coding Technique of still Images", Journal of Television Society of Japan, Vol. 44, No. 2 (1990), a report by Hiroshi Ochi, et al., "International Standard Trend of Still Image Coding", Proceedings No. 14 for National Meeting of Image Electronic Society of Japan, 1988, etc.
FIG. 2 is a block diagram schematically showing a configuration of the highly efficient coding circuit for images using the ADCT method.
In FIG. 2, an image signal applied to a terminal 111 is given by a string of digital data which has been converted into 8 bits, i.e., 256 gradations/color, in the A/D converter 102 in FIG. 1. The number of colors is three or four such as represented by RGB, YUV, YP.sub.b P.sub.r or YMCK.
The input digital image signal is immediately subjected to two-dimensional discrete cosine transform (hereinafter abbreviated as DCT) in a DCT transformer 112 in units of subblock comprising (8.times.8) pixels.
The DCT-transformed data of (8.times.8) words (hereinafter referred to as conversion coefficients) are quantized in a linear quantization circuit 113 with quantizing step sizes being different for every conversion coefficients. Thus, the quantizing step sizes for respective conversion coefficients are given by values output from a multiplier 116 which multiplies quantizing matrix elements of (8.times.8) from a quantizing matrix generator 114 by 2.sup.S.
The quantizing matrix elements are determined in consideration of the fact that visual sensitivity for quantizing noise is different for each of the conversion coefficients of (8.times.8) words. One example of the quantizing matrix elements is shown in Table 1 below.
On the other hand, the data of 2.sup.S is obtained from a data generator 115 and the value of S is O or a positive or negative integer called a scaling factor. The image quality or the amount of data is controlled depending on the value of S.
TABLE 1 ______________________________________ One Example of Quantizing Matrix Elements ______________________________________ 16 11 10 16 24 40 51 61 12 12 14 19 26 58 60 55 14 13 16 24 40 57 69 56 14 17 22 29 51 87 80 62 18 22 37 56 68 109 103 77 24 35 55 64 81 104 113 92 49 64 78 87 103 121 120 101 72 92 95 98 112 100 103 99 ______________________________________
DC components of the respective quantized conversion coefficients, i.e., DC conversion coefficients in the matrix of (8.times.8) (hereinafter referred to as DC components), are supplied to a one-dimensional prediction .difference circuit 117, and prediction errors obtained by the circuit 117 are subjected to Huffman coding in a Huffman coding circuit 118. More specifically, after dividing quantized outputs of the prediction errors into groups, the ID numbers of the groups to which the respective prediction errors belong are first subjected to Huffman coding, and which values in each groups correspond to the respective prediction errors are then represented by using equi-length codes.
The conversion coefficients other than the above DC components, i.e., the AC conversion coefficients (hereinafter referred to as AC components), are supplied to a zigzag scanning circuit 119 in which the AC components are scanned in a zigzag manner with two-dimensional frequencies from low-frequency component to high-frequency component as shown in FIG. 3. The circuit 119 outputs, to a Huffman coding circuit 120, a combination of those conversion coefficients for which the quantized outputs are not 0 (hereinafter referred to as significant coefficients), and the number (run-length) of those conversion coefficients which are present between the just preceding significant coefficient and the present significant coefficient and for which the quantized outputs are 0 (hereinafter referred to as insignificant coefficients).
The Huffman coding circuit 120 divides the AC components into groups depending on the values of the significant coefficients. The ID numbers of these groups and the respective run-lengths are subjected to Huffman coding in pair, and which values in each group correspond to the respective significant coefficients are then represented by using equi-length codes.
Outputs of the Huffman coding circuits 118, 120 are multiplexed in a multiplexing circuit 121 and supplied as a coded output to a downstream error correction coding circuit 104 from a terminal 122.
With the highly efficient coding as mentioned above, no deterioration of images is found and extremely efficient compression can be performed even when the amount of information is compressed to fractional parts of the original amount.
However, in the system adapted for such superior compression efficiency, i.e., compression of information at a high compression rate, one code error poses a serious influence upon an image.
Where the system is designed to carry out the variable length coding as set forth above, for example, a code error may lead to incapability of the subsequent decoding process, resulting in that images after occurrence of the error are so disturbed as to look very indistinct or awkward.
Further, in the system of performing the compression at such a high compression rate, if a correction impossible error occurs in key codes for the decoding process, reproduced images generally suffer from a fatal failure.
Particularly, that type system has also been recently employed for those transmission lines in which transmission quality may be changed and deteriorated depending on weather conditions, as represented by communication satellites. It is therefore needed for measures capable of protecting data against errors occurring on transmission lines.
However, simply stepping up the measures to prevent errors merely results in the increased redundancy of codes. This means that the advantage of image compression made with high efficiency using the advanced technique is canceled out.
Such simple step-up also prolongs the length of code, such as an error detection code and an error correction code relatively, which in turn complicates arithmetic operations necessary in both the coding and decoding processes. This eventually increases the structural size of hardware or prevents a reduction of the processing time, and thus impedes wider practical use of the system as stated above.